As a companion project to Dr. Kleerekoper's clinical prevention study of hip fracture and estrogen replacement therapy (ERT) (RFA AG91-04), this application seeks support to collect and analyze data which describes the internal bone architecture and overall geometry of the proximal femur. A Computed Tomography (CT) technique will be used which produces a fine three-dimensional (3D) array of bone density values, unaffected by the absolute or relative orientation of the subject Baseline and annual studies will be obtained on all 210 subjects recruited. Sophisticated algorithms which realign the 3D data obtained serially provides very consistent architecture measures. Regional density values will be determined for specific volumes of both cancellous and cortical bone tissue. These specific questions will be directly addressed by this project in combination with a related research grant (R29-AG08776-02): 1. Is there a typical pattern of regional bone mineral density in the proximal femur for older (skeletally healthy) women? How do the architectural parameters measured by the 3D-CT technique relate to the 2D- DXA (dual-energy x-ray absorptiometry) results? 2. What is the typical change over time of this density pattern? Do elements of structural geometry affect bone loss patterns and/or rates? How do rates of cortical and cancellous bone loss differ? 3. Is this typical bone loss pattern altered by the proposed clinical intervention (ERT)? 4. Are the density patterns observed in this group different from those of a population who have sustained a Type II Osteoporotic hip fracture? Can a vulnerable proximal femur architecture be recognized early, thus allowing the discrimination of those patients at the highest risk of fracture to be clinically treated? 5. Do the bone loss patterns appear to be changing the bone density distribution toward the Typica Osteoporosis group architecture? Are there varying rates of bone loss across the postmenopausal population in the proximal femur? Can a subgroup of women with high bone loss rates be identified to further focus our treatment to those most likely to benefit?